Pranjal Sahu is a Senior Scientist specializing in deep learning for medical imaging, with 11 years of experience applying CNNs, Transformers, GANs and few-shot methods to problems from chest X-ray abnormality detection to 3D CT segmentation. He leads chest X-ray auto-reporting and lesion-detection efforts at Siemens Healthineers, where models he helped develop have passed reader studies in the U.S. and are in FDA submission. Pranjal combines research rigor (PhD from Stony Brook) with production engineering—building end-to-end ML pipelines, Python/C++ integrations and distributed workflows—to scale training and deployment on large multi-modal datasets. His open-source contributions to the Insight Toolkit (ITK) include robust mesh-module improvements (Gaussian curvature, serialization tests, memory-leak fixes), highlighting a strong backend and testing orientation often overlooked in imaging researchers. Comfortable with LLM finetuning, Dask, and clinical-scale evaluations, he bridges algorithmic innovation and regulatory-ready productization. Based in Princeton, he maintains an active GitHub and homepage showcasing publications and tooling that support both research and clinical translation.
11 years of coding experience
6 years of employment as a software developer
Bachelor of Technology (B.Tech.), Computer Science and Engineering, 8.35, Bachelor of Technology (B.Tech.), Computer Science and Engineering, 8.35 at Indian Institute of Technology, Kharagpur
Doctor of Philosophy (Ph.D.), Computer Science, 3.87, Doctor of Philosophy (Ph.D.), Computer Science, 3.87 at Stony Brook University
Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
Role in this project:
Backend Developer & Test Automation Engineer
Contributions:62 reviews, 64 commits, 49 PRs in 11 months
Contributions summary:Pranjal's commits primarily focused on enhancing the ITK Mesh module. They implemented a Gaussian Curvature Calculator in the ITK Mesh, including associated tests and Python wrapping. The contributions included adding tests for non-triangle meshes, refining cell casting, and addressing memory leaks. Further efforts involved improving the test suite by adding tests for mesh serialization and various mesh types.
Contributions:14 commits, 13 pushes, 1 branch in 5 months
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Pranjal Sahu - Senior Scientist at Siemens Healthineers